IDEAS home Printed from https://ideas.repec.org/p/ags/semrui/186383.html
   My bibliography  Save this paper

Quantifying the uncertainty of wave energy conversion device cost for policy appraisal: an Irish case study

Author

Listed:
  • Farrell, N.
  • O'Donoghue, C.
  • Morrissey, K.

Abstract

Wave Energy Conversion (WEC) devices are at a pre-commercial stage of development with feasibility studies sensitive to uncertainties surrounding assumed input costs. This may affect decision-making. This paper analyses the impact these uncertainties may have on investor, developer and policymaker decisions using an Irish case study. Calibrated to data present in the literature, a probabilistic methodology is shown to be an effective means to carry this out. Value at Risk (VaR) and Conditional Value at Risk (CVaR) metrics are used to quantify the certainty of achieving a given cost or return on investment. The certainty of financial return offered by proposed Irish Feed-in Tariff (FiT) policy is analysed. The influence of technological ‘learning’ is also discussed. The model presented identifies those rates of learning required to achieve cost-effective deployment under various cost certainty requirements. The corresponding cost reduction targets for developers are identified. Uncertainty is found to have a greater impact on the investment decision when learning progresses at a slower rate. This paper emphasises the requirement for a premium to account for cost uncertainty when setting FiT rates. By quantifying uncertainty, the presented methodology allows for the required premium to be identified.

Suggested Citation

  • Farrell, N. & O'Donoghue, C. & Morrissey, K., 2014. "Quantifying the uncertainty of wave energy conversion device cost for policy appraisal: an Irish case study," Working Papers 186383, National University of Ireland, Galway, Socio-Economic Marine Research Unit.
  • Handle: RePEc:ags:semrui:186383
    DOI: 10.22004/ag.econ.186383
    as

    Download full text from publisher

    File URL: http://ageconsearch.umn.edu/record/186383/files/14-WP-SEMRU-02.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Pelc, Robin & Fujita, Rod M., 2002. "Renewable energy from the ocean," Marine Policy, Elsevier, vol. 26(6), pages 471-479, November.
    2. Gass, V. & Strauss, F. & Schmidt, J. & Schmid, E., 2011. "Assessing the effect of wind power uncertainty on profitability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 2677-2683, August.
    3. O. Scaillet, 2004. "Nonparametric Estimation and Sensitivity Analysis of Expected Shortfall," Mathematical Finance, Wiley Blackwell, vol. 14(1), pages 115-129, January.
    4. Allan, Grant & Gilmartin, Michelle & McGregor, Peter & Swales, Kim, 2011. "Levelised costs of Wave and Tidal energy in the UK: Cost competitiveness and the importance of "banded" Renewables Obligation Certificates," Energy Policy, Elsevier, vol. 39(1), pages 23-39, January.
    5. Montes, German Martinez & Martin, Enrique Prados & Bayo, Javier Alegre & Garcia, Javier Ordoñez, 2011. "The applicability of computer simulation using Monte Carlo techniques in windfarm profitability analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4746-4755.
    6. Guanche, R. & de Andrés, A.D. & Simal, P.D. & Vidal, C. & Losada, I.J., 2014. "Uncertainty analysis of wave energy farms financial indicators," Renewable Energy, Elsevier, vol. 68(C), pages 570-580.
    7. Leete, Simeon & Xu, Jingjing & Wheeler, David, 2013. "Investment barriers and incentives for marine renewable energy in the UK: An analysis of investor preferences," Energy Policy, Elsevier, vol. 60(C), pages 866-875.
    8. O'Connor, M. & Lewis, T. & Dalton, G., 2013. "Operational expenditure costs for wave energy projects and impacts on financial returns," Renewable Energy, Elsevier, vol. 50(C), pages 1119-1131.
    9. Dalton, G.J. & Alcorn, R. & Lewis, T., 2010. "Case study feasibility analysis of the Pelamis wave energy convertor in Ireland, Portugal and North America," Renewable Energy, Elsevier, vol. 35(2), pages 443-455.
    10. O'Connor, M. & Lewis, T. & Dalton, G., 2013. "Weather window analysis of Irish west coast wave data with relevance to operations & maintenance of marine renewables," Renewable Energy, Elsevier, vol. 52(C), pages 57-66.
    11. Dunnett, David & Wallace, James S., 2009. "Electricity generation from wave power in Canada," Renewable Energy, Elsevier, vol. 34(1), pages 179-195.
    12. Falconett, Irina & Nagasaka, Ken, 2010. "Comparative analysis of support mechanisms for renewable energy technologies using probability distributions," Renewable Energy, Elsevier, vol. 35(6), pages 1135-1144.
    13. AfDB AfDB, . "AfDB Group Annual Report 2011," Annual Report, African Development Bank, number 392.
    14. Conor Devitt & Laura Malaguzzi Valeri, 2011. "The Effect of REFIT on Irish Wholesale Electricity Prices," The Economic and Social Review, Economic and Social Studies, vol. 42(3), pages 343-369.
    15. Junginger, M. & Faaij, A. & Turkenburg, W. C., 2005. "Global experience curves for wind farms," Energy Policy, Elsevier, vol. 33(2), pages 133-150, January.
    16. Yang, Ming & Nguyen, François & De T'Serclaes, Philippine & Buchner, Barbara, 2010. "Wind farm investment risks under uncertain CDM benefit in China," Energy Policy, Elsevier, vol. 38(3), pages 1436-1447, March.
    17. Montes, Germán Martínez & Martín, Enrique Prados, 2007. "Profitability of wind energy: Short-term risk factors and possible improvements," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(9), pages 2191-2200, December.
    18. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    19. Dalton, G.J. & Alcorn, R. & Lewis, T., 2012. "A 10 year installation program for wave energy in Ireland: A case study sensitivity analysis on financial returns," Renewable Energy, Elsevier, vol. 40(1), pages 80-89.
    20. Teillant, Boris & Costello, Ronan & Weber, Jochem & Ringwood, John, 2012. "Productivity and economic assessment of wave energy projects through operational simulations," Renewable Energy, Elsevier, vol. 48(C), pages 220-230.
    21. AfDB AfDB, . "AfDB Group Annual Report 2011 (Arabic)," Annual Report, African Development Bank, number 394.
    22. Unknown, 2012. "2012 Annual Agricultural Outlook," Staff Paper Series 120986, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    23. O'Connor, M. & Lewis, T. & Dalton, G., 2013. "Techno-economic performance of the Pelamis P1 and Wavestar at different ratings and various locations in Europe," Renewable Energy, Elsevier, vol. 50(C), pages 889-900.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. John Hutcheson & Adrián De Andrés & Henry Jeffrey, 2016. "Risk vs. Reward: A Methodology to Assess Investment in Marine Energy," Sustainability, MDPI, Open Access Journal, vol. 8(9), pages 1-44, August.
    2. Ramos, V. & Ringwood, John V., 2016. "Exploring the utility and effectiveness of the IEC (International Electrotechnical Commission) wave energy resource assessment and characterisation standard: A case study," Energy, Elsevier, vol. 107(C), pages 668-682.
    3. Adrian De Andres & Jéromine Maillet & Jørgen Hals Todalshaug & Patrik Möller & David Bould & Henry Jeffrey, 2016. "Techno-Economic Related Metrics for a Wave Energy Converters Feasibility Assessment," Sustainability, MDPI, Open Access Journal, vol. 8(11), pages 1-19, October.
    4. Foteinis, S. & Tsoutsos, T., 2017. "Strategies to improve sustainability and offset the initial high capital expenditure of wave energy converters (WECs)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 775-785.
    5. Niall Farrell & Cathal O'Donoghue & Karyn Morrissey, 2020. "Regional income and wave energy deployment in Ireland," Papers in Regional Science, Wiley Blackwell, vol. 99(3), pages 509-531, June.

    More about this item

    Keywords

    Environmental Economics and Policy;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:semrui:186383. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search). General contact details of provider: http://edirc.repec.org/data/semgaie.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.